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387 articles for “AI accuracy”
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A Reviewed Study On Cpu-Optimized Parameter-Efficient Fine- Tuning For Large Language Models To Increase Accuracy Using Lora
Abstract: The fast proliferation of Large Language Models (LLMs) has increased the need to optimize the process of fine-tuning but the existing workflows that require a GPU are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of Parameter-Efficient Fine-Tuning (PEFT) based on Low-Rank Adaptation (LoRA). The major purpose of the study …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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An Expected Cardiovascular Disease Detection Using Deep Learning Techniques
Abstract: Many avoidable deaths globally are caused by CVD, often due to individuals remaining unaware of their risk factors until severe symptoms, such as heart attacks or strokes, appear. This study utilizes retinal images as the dataset to explore the potential of retinal imaging as a non-invasive diagnostic tool for early detection of cardiovascular diseases (CVD). The delay in diagnosis and treatment highlights the need for sophisticated diagnostic instruments that can …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 Read article
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Plc Hmi base testing machine data loger with usb excel data export
Abstract: The PLC-HMI-based testing machine data logger is designed to acquire, process, and log real-time sensor data using a PLC analog input card. This system is developed for industrial applications requiring accurate measurement, monitoring, and data storage. The setup integrates an HMI (Human-Machine Interface) for visualization and control, while a USB-based Excel data export feature ensures efficient data management. The system incorporates four key transducers: 1. Water Flow Sensor – Measures …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 Read article
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AI-Based Preventive Healthcare Using Quantum Computing
Abstract: With its improved performance and capabilities, quantum machine learning (QML) is becoming a promising field, especially in the healthcare industry for tasks like early heart disease prediction. In this work, a Quantum Support Vector Classifier (QSVC) is proposed as the basic classifier for a bagging ensemble learning model. Shapley Additive explanations (SHAP) are used to evaluate the significance of each attribute in the predictions in order to improve explainability. Using …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article
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Automated Car License Plate Detection and Recognition Using Deep Learning
Abstract: The use of automated license plate detection and recognition (ALPR) systems to automate processes such as number plate detection is gaining popularity in traffic control, security, and law enforcement. This research focuses on achieving more accurate and efficient detection and recognition of number plates by leveraging deep learning techniques. The systems outlined in this study aim to improve the effectiveness of ALPR systems using advanced convolutional neural networks (CNNs) and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 23–29 Read article
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CFD Analysis: Double Pipe Heat Exchanger, Latent Heat Storage, and BIM-CFD Integration
Abstract: This is a review work covering four research papers. Heat exchangers transport thermal energy across fluids; research in SolidWorks 2014 compared flow simulation to the effectiveness-NTU approach. Slow PCM charging/discharging is a global concern in latent heat storage; research on the influence of flow rate and temperature on melting and solidification durations discovered efficiency in a triple tube heat exchanger design. Advances in computational fluid dynamics for forecasting separated flows …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 2, 2024 · pp. 19–24 Read article
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A Comprehensive Study of Natural Language Processing Systems Using Modern Programming Languages: Techniques, Architectures, Experimental Evaluation, and Applications
Abstract: Natural Language Processing is a key field of study within artificial intelligence that focuses on enabling machines to understand and work with human language. This is because there is much digital text data everywhere. Natural Language Processing is what this study is about. It looks at new ways of doing Natural Language Processing. The old ways are like machine learning and the new ways are like learning. This study compares …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article
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Discovery Tools and Services for Libraries: Transforming Access to Knowledge in the Digital Age
Abstract: The digital transformation of libraries has led to the emergence of discovery services as pivotal tools for enhancing resource accessibility, usability, and research efficiency. This article explores the evolution, functionality, and impact of discovery services in academic and public libraries. Unlike traditional online public access catalogues (OPACs), discovery services consolidate diverse information sources—such as books, journals, databases, institutional repositories, and open-access content—into a single, user-friendly interface. By integrating advanced technologies …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 1, 2025 · pp. 51–56 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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Learning of Maximum Power Point Tracking Architecture with Various Algorithms for Photovoltaic Systems: A Review
Abstract: Currently, as the requirement on the Earth for ever more electricity grows, so too accordingly must demands upon renewable energy. These days, with the growth of renewable energy on all fronts, countries everywhere watch its development. Since demand for power generation goes up again, fossil fuels become less and less available, and expense is not coming down. When there is a rapidly changing irradiance, temperature, or partial shading, the output …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 2, 2026 Read article
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Influence of Carbonyl Iron Particle Loading on the Dimensional and Rheological Properties of 4D-Printed TPU-Based Magnetorheological Elastomers
Abstract: The advancement of 4D printing technologies has created new opportunities for fabricating smart materials with tunable properties, including magnetorheological elastomers (MREs). This study investigates the fabrication and characterization of thermoplastic polyurethane (TPU)-based MREs with varying carbonyl iron particle (CIP) loadings (10–50 wt.%) using the fused filament fabrication (FFF) method. MRE filaments were produced through a solvent-assisted mixing and extrusion process, ensuring consistent diameters within 1.75 ± 0.10 mm. Test specimens …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 127–138 Read article
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Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article
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Analysis of White Matter, Gray Matter, and Cerebrospinal Fluid Alterations in Neurological Disorders: A Deep Learning Approach
Abstract: This paper investigates the role of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) alterations in the pathophysiology of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, schizophrenia, and epilepsy. By leveraging advanced deep learning methodologies, we aim to automate the segmentation and analysis of brain structures from MRI scans, enabling a more detailed and precise evaluation of their roles in disease progression. These techniques allow for the identification …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 3, 2024 · pp. 21–27 Read article
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Smart Protective System for EVs
Abstract: Electric vehicles, or EVs, form the bedrock of sustainable transportation, offering both energy efficiency and low carbon emissions. However, the safety issues emanating from the complexity of road conditions call for innovative solutions. This paper introduces a Smart Protective System for EVs, integrating YOLOv5 for real-time obstacle and pothole detection with ultrasonic sensors for proximity measurement. The system is able to achieve an object detection accuracy of 95% under normal …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 8–14 Read article
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Predictive Maintenance Strategies for Safety-critical Mechanical Systems
Abstract: Ensuring the reliability and safety of industrial systems is essential, especially in high-risk sectors such as aerospace, manufacturing, and energy. Predictive maintenance (PdM) has become a crucial approach for minimizing operational failures and improving maintenance efficiency. This research introduces an advanced PdM framework that enhances industrial safety by integrating Internet of Things (IoT) technology, machine learning (ML), and big data analytics. By enabling real-time monitoring and predictive fault detection, this …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 12–17 Read article
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Different NLP Libraries for Indian Languages
Abstract: Humans are by nature varied and multilingual. While English holds the title of the most commonly spoken language globally, Hindi is also widely used by people worldwide. Natural language processing (NLP) is the discipline of artificial intelligence (AI) concerned with providing computers the capacity to interpret text and spoken language in the same manner that humans can. People nowadays utilize products that employ NLP as their foundation, such as Alexa …
Published in Journal of Open Source Developments · Vol. 11, Issue 1, 2024 · pp. 8–14 Read article
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Nanoparticle-Based Early Diagnostic Tools for Tuberculosis and Malaria in Rural India
Abstract: Malaria and Tuberculosis continue to be two major public health challenges in rural India. The interplay between an inefficient health care system, late diagnosis, and under-identification of cases contributes to the high morbidity and mortality associated with TB and Malaria. Conventional methods, such as sputum microscopy for TB, microscopy and rapid diagnostic tests (RDTs) for malaria, have a higher benchmark of sensitivity that requires a certain amount of time, skilled …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 45–51 Read article
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Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
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Stock Market Prediction Using Machine Learning: Techniques, Challenges, and Future Directions
Abstract: The continuous advancement of machine learning (ML) technologies has significantly transformed the field of financial forecasting, particularly in the area of stock market prediction. The ability to accurately forecast stock price movements and market trends plays a crucial role in supporting informed investment strategies and effective risk management. This paper provides a comprehensive review of recent developments in the application of ML techniques for predicting stock market behavior. It classifies …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 10–16 Read article
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User Review-Driven Recommendation Model for E-Scooter Selection
Abstract: In the era of rising environmental awareness and the growing emphasis on sustainable mobility practices, electric scooters (e-scooters) have gained significant popularity as an efficient and eco-friendly alternative to conventional modes of transport. Their ability to reduce carbon emissions, minimize traffic congestion, and offer cost-effective commuting solutions has made them highly attractive, particularly in urban environments. However, with the rapid expansion of the e-scooter market, consumers are faced with an …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 6–16 Read article